US7810376B2 - Mitigation of gas memory effects in gas analysis - Google Patents
Mitigation of gas memory effects in gas analysis Download PDFInfo
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- US7810376B2 US7810376B2 US11/983,128 US98312807A US7810376B2 US 7810376 B2 US7810376 B2 US 7810376B2 US 98312807 A US98312807 A US 98312807A US 7810376 B2 US7810376 B2 US 7810376B2
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/28—Preparing specimens for investigation including physical details of (bio-)chemical methods covered elsewhere, e.g. G01N33/50, C12Q
- G01N1/40—Concentrating samples
- G01N1/405—Concentrating samples by adsorption or absorption
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N7/00—Analysing materials by measuring the pressure or volume of a gas or vapour
- G01N7/02—Analysing materials by measuring the pressure or volume of a gas or vapour by absorption, adsorption, or combustion of components and measurement of the change in pressure or volume of the remainder
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/02—Devices for withdrawing samples
- G01N1/22—Devices for withdrawing samples in the gaseous state
- G01N1/2247—Sampling from a flowing stream of gas
- G01N2001/2264—Sampling from a flowing stream of gas with dilution
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/28—Preparing specimens for investigation including physical details of (bio-)chemical methods covered elsewhere, e.g. G01N33/50, C12Q
- G01N1/38—Diluting, dispersing or mixing samples
- G01N2001/386—Other diluting or mixing processes
- G01N2001/387—Other diluting or mixing processes mixing by blowing a gas, bubbling
Definitions
- This invention relates to gas handling for gas analysis.
- the “memory effect” is a well-known problem in the art, in which the measured analyte concentration can undesirably depend on the past history of the measurement system. For example, if the analyte concentration starts out high and then abruptly decreases to a much lower level, the gas analysis sensor may provide erroneously high analyte readings for some time after the analyte concentration decreases.
- the memory effect is especially severe for sticky analytes, such as water vapor or ammonia.
- the analyte can be adsorbed onto surfaces of the sample chamber and/or gas delivery system.
- the analyte can also be dissolved (i.e., absorbed) into parts of the sample chamber and/or delivery system.
- the gas absorption/adsorption memory effect in gas analysis can be reduced by controlling gas flow conditions such that the partial pressure of the analyte of interest is held constant, provided the analyte concentration presented for analysis is within a predetermined range. Keeping the analyte partial pressure constant is helpful for mitigating the memory effect because changes in analyte absorption/adsorption rates tend to be driven by changes in analyte partial pressure.
- the analyte partial pressure can be held constant by altering the total pressure in the gas sample chamber and/or by admitting a known fraction of inert gas to the sample chamber, where the inert gas is known not to include the analyte of interest.
- the memory effect can also be mitigated by performing concentration measurements at two or more different gas flow rate conditions, and employing a mathematical model to estimate true concentration and “memory effect” contributions to measured concentrations at one or more of the flow rate conditions.
- the mathematical model can be based on an assumption that the true analyte concentration presented for analysis is independent of flow rate, while the “memory effect” contribution to the observed concentration is inversely proportional to flow rate.
- Another option is to base the mathematical model on an assumption that the true analyte concentration is independent of total pressure in the sample chamber, while the “memory effect” contribution to the observed concentration is inversely proportional to total pressure in the sample chamber.
- FIG. 1 shows a gas handling system according to a first embodiment of the invention.
- FIG. 2 shows a gas handling system according to a second embodiment of the invention.
- FIG. 3 shows a gas handling system according to a third embodiment of the invention.
- FIG. 1 shows a gas handling system according to a first embodiment of the invention.
- the example of FIG. 1 includes a sample chamber 106 capable of admitting sample gas for analysis from a sample gas source 102 .
- a gas analyte sensor 108 is operatively connected to sample chamber 106 and is capable of measuring analyte concentration or analyte partial pressure in the sample gas.
- a pressure sensor 116 measures the total gas pressure in sample chamber 106 . Knowledge of the total gas pressure in sample chamber 106 allows analyte concentration to be determined from analyte partial pressure, or vice versa.
- sensor 108 directly provides a partial pressure measurement.
- a gas flow controller is also included, which is capable of altering the analyte partial pressure in sample chamber 106 .
- the gas flow controller includes a controller 114 connected to an inlet flow controller 104 and an outlet flow controller 110 . Gas emitted from outlet flow controller 110 is received by an exhaust subsystem 112 .
- the reduced memory effect provided by embodiments of the invention is especially beneficial for ultra-sensitive gas sensors 108 , including but not limited to sensors based on: cavity ring-down spectroscopy (CRDS); other forms of cavity-enhanced absorption spectroscopy (CEAS) such as (off-axis) integrated cavity output spectroscopy (ICOS, OA-ICOS); evanescent wave spectroscopy such as using an optical fiber, micro-resonator (whispering gallery mode resonator), or CRDS (EW-CRDS); adsorption-reflection spectroscopy; and non-optical detection methods.
- CRDS cavity ring-down spectroscopy
- CEAS cavity-enhanced absorption spectroscopy
- CEAS integrated cavity output spectroscopy
- evanescent wave spectroscopy such as using an optical fiber, micro-resonator (whispering gallery mode resonator), or CRDS (EW-CRDS); adsorption-reflection spectroscopy;
- the memory effect is mitigated by configuring the gas flow controller to maintain the partial pressure of the analyte being monitored substantially constant by altering the total pressure, provided the analyte concentration in the gas from sample gas source 102 is within a predetermined control range. For example, suppose the nominal operating total pressure of a gas analyzer for monitoring ammonia is 200 Torr and the nominal ammonia concentration being monitored is 10 ppbv (i.e., the nominal ammonia partial pressure P a is 2 ⁇ 10 ⁇ 6 Torr).
- M c the ammonia concentration of gas from sample gas source 102 in ppbv.
- the ammonia partial pressure P a is 2 ⁇ 10 ⁇ 6 Torr (i.e., it is held constant). If the concentration in gas from the sample gas source falls outside the predetermined range, the total pressure can be set to some nominal or default value (i.e., 200 Torr in this example). In cases in which the analyte concentration in gas from the sample gas source falls outside the predetermined control range, mitigation of the memory effect does not occur.
- Arranging the system such that the partial pressure of the analyte of interest is held constant advantageously mitigates the memory effect, since changes in absorption/adsorption rates tend to be driven by changes in partial pressure.
- a state of dynamic equilibrium can be reached or approached, where the net absorption/adsorption rate of the analyte is relatively low.
- the memory effect is advantageously reduced.
- FIG. 2 shows a gas handling system according to an embodiment of the invention where such mixing is employed. This embodiment is similar to the embodiment of FIG. 1 , except that the gas flow controller in the example of FIG. 2 includes a mixer 204 capable of providing a mixture of the sample gas and an inert gas from inert gas source 202 to sample chamber 106 .
- the inert gas preferably does not include any species that could erroneously register as the analyte of interest in sensor 108 . In this case, the concentration of analyte in the gas provided by sample gas source 102 equals P a /(R ⁇ P t ).
- a nominal ammonia partial pressure for ammonia monitoring is 10 ⁇ 6 Torr at a fixed total pressure of 100 Torr. If the ammonia concentration in the sample gas is 20 ppbv, R should be 0.5 to keep the ammonia partial pressure equal to 10 ⁇ 6 Torr. If the ammonia concentration in the sample gas is 80 ppbv, R should be 0.125 to keep the ammonia partial pressure equal to 10 ⁇ 6 Torr.
- the predetermined control range is 20 ppbv to 80 ppbv
- the inert gas fraction is 1-R.
- One feature of this example is that the operating pressure in sample chamber 106 is held constant as the sample gas fraction is varied.
- the partial pressure constant by both altering the total pressure in the sample chamber and altering a known fraction of inert gas in the sample chamber.
- the range of measured analyte concentrations i.e., the control range
- the concentration of analyte in the sample gas provided by gas source 102 equals P a /(R ⁇ P t ), where both R and P t can vary in chamber 106 .
- the analyte concentration in chamber 106 may or may not be the same as the analyte concentration in the gas provided by sample gas source 102 .
- FIG. 3 shows a gas handling system according to an embodiment of the invention in which such processing is performed.
- FIG. 3 is similar to the example of FIG. 1 , except that a processor 302 is connected to sensor 108 on FIG. 3 .
- Processor 302 is capable of providing estimates for true analyte concentration of the sample gas source 102 and memory effect contribution to the analyte concentration in chamber 106 based on measurements performed at two or more distinct gas flow conditions.
- Gas flow conditions can be described in terms of gas flow parameters, such as pressure, flow rate, and temperature in the sample chamber.
- Processor 302 can be any combination of hardware and/or software. Determination of the true and “memory effect” analyte concentrations is based on a mathematical model, which can be provided to the process as a corresponding algorithm. Various mathematical models can be employed in practicing embodiments of the invention.
- the mathematical model can be based on assuming the true analyte concentration is independent of flow rate and that the “memory effect” contribution to analyte concentration is inversely proportional to flow rate, F, while keeping the total pressure, P t , constant.
- 10 ppbv of analyte is measured at total pressure P 1
- 7 ppbv of analyte is measured shortly thereafter at pressure 2P 1 .
- the quantities A m and B m change over time, approaching zero until the flow condition is changed, at which time they assume new values according to the new flow condition and again decay in time.
- the decay can usually be accurately modeled by an exponential function. If significant decay of A m or B m occurs between measurements of M s , the equations in the above two paragraphs should be modified to include the effect of the decay.
- the decay rate (if it is exponential) may be taken as a predetermined fixed value, or determined from measurements of M s in time.
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US11/983,128 US7810376B2 (en) | 2007-11-06 | 2007-11-06 | Mitigation of gas memory effects in gas analysis |
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Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20110199611A1 (en) * | 2010-02-16 | 2011-08-18 | Honeywell International Inc. | Detector for cavity ring-down spectroscopy |
US9012851B2 (en) | 2010-10-14 | 2015-04-21 | Thermo Fisher Scientific (Bremen) Gmbh | Optical chamber module assembly |
US9651488B2 (en) | 2010-10-14 | 2017-05-16 | Thermo Fisher Scientific (Bremen) Gmbh | High-accuracy mid-IR laser-based gas sensor |
US11493409B2 (en) * | 2019-12-08 | 2022-11-08 | Alti Llc | Field sampling system and method of using |
Families Citing this family (6)
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US20090323055A1 (en) * | 2008-06-25 | 2009-12-31 | Honeywell International Inc. | Crds brewster gas cell |
US8269972B2 (en) | 2010-06-29 | 2012-09-18 | Honeywell International Inc. | Beam intensity detection in a cavity ring down sensor |
US8437000B2 (en) | 2010-06-29 | 2013-05-07 | Honeywell International Inc. | Multiple wavelength cavity ring down gas sensor |
US8322191B2 (en) | 2010-06-30 | 2012-12-04 | Honeywell International Inc. | Enhanced cavity for a photoacoustic gas sensor |
GB2537914B (en) * | 2015-04-30 | 2019-03-20 | Thermo Fisher Scient Bremen Gmbh | Flow reduction system for isotope ratio measurements |
CN114839159B (en) * | 2022-04-13 | 2023-06-02 | 中国空气动力研究与发展中心超高速空气动力研究所 | Resonant cavity absorption spectrum measuring method compatible with cavity enhancement technology and cavity ring-down technology |
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US9012851B2 (en) | 2010-10-14 | 2015-04-21 | Thermo Fisher Scientific (Bremen) Gmbh | Optical chamber module assembly |
US9651488B2 (en) | 2010-10-14 | 2017-05-16 | Thermo Fisher Scientific (Bremen) Gmbh | High-accuracy mid-IR laser-based gas sensor |
US20170248517A1 (en) * | 2011-09-09 | 2017-08-31 | Thermo Fisher Scientific (Bremen) Gmbh | High-accuracy mid-ir laseer-based gas sensor |
US10107751B2 (en) * | 2011-09-09 | 2018-10-23 | Thermo Fisher Scientific (Bremen) Gmbh | High-accuracy mid-IR laser-based gas sensor |
US10295464B2 (en) | 2011-09-09 | 2019-05-21 | Thermo Fisher Scientific (Bremen) Gmbh | High-accuracy mid-IR laser-based gas sensor |
US11493409B2 (en) * | 2019-12-08 | 2022-11-08 | Alti Llc | Field sampling system and method of using |
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US20090113988A1 (en) | 2009-05-07 |
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